Fish_Stuff
Callie Stephenson
2024-03-28
knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)TIDY DATA:
First chunk of code subsets to only using 8 blocks per survey location, 4 from an ‘on’ and 4 from an ‘adjacent’. I also remove pins where camera malfunctions made this not possible (Pin 13 and Pin 2).
Since we could count some species as distinct individuals by life stages, I have combined those counts together here:
And built a little code to double check that it went correctly (should create two empty data frames)
I then deal with extreme schooling events following methods from the Donovan regimes paper: “Additional methodology was developed for dealing with outliers in the fish data, accounting for extreme observations of schooling species. Extreme observations in the database were defined by calculating the upper 99.9% of all individual observations (e.g. one species, size and count on an individual transect), resulting in 26 observations out of over 0.5 million, comprised of 11 species. The distribution of individual counts in the entire database for those 11 species was then used to identify observations that fell above the 99.0% quantile of counts for each species individually. These observations were adjusted to the 99.0% quantile for analysis.”
and ending by renaming the dataframe as just fish_tidy for future use: this allows me to make extra tidy data adjustments without breaking the dataframe name later on in the code!
Data Vis
Linda from Johanssen Lab reccommended to make a plot that is ordered by the most abundant fish near the seep and look for any patterns, so I went and made this plot a number of ways. First, I kept all the species and looked a just the average abundance at all pins, to see if the communities looked relatively similar in this way.
All species average abundance across gradient
This is too busy to read, and no major patterns jump out. I subset this to just the top 20 species along the gradient, and again the order of the pins does not have biological relevance.
Most common 20 species average abundance across gradient
So, now I will order the pins by those most common at pin 14
This isn’t showing the most obvious patterns, but there were only a few species of fish that swam in the sane near the seep. So, I’ll reorder the pins by the distance to the seep
Most common species average abundance at each pin by distance to seep:
To see if maybe a nutrient parameter would be good desciptor, I do this also by the low tide mean silicate
Most common species average abundance across the gradient of low tide mean silicate
Most common species average abundance across the gradient of nutrient delivery
Nutrient delivery quantified as a pc axis I got from the low tide mean of major nutrients across the gradient.
NMDS
Code from Linda:
## Run 0 stress 0.220305
## Run 1 stress 0.2229423
## Run 2 stress 0.2180258
## ... New best solution
## ... Procrustes: rmse 0.04630299 max resid 0.4167562
## Run 3 stress 0.219145
## Run 4 stress 0.2178598
## ... New best solution
## ... Procrustes: rmse 0.04508706 max resid 0.4190789
## Run 5 stress 0.224903
## Run 6 stress 0.2271076
## Run 7 stress 0.2264543
## Run 8 stress 0.2179119
## ... Procrustes: rmse 0.02674603 max resid 0.1311672
## Run 9 stress 0.2277538
## Run 10 stress 0.2232015
## Run 11 stress 0.2268599
## Run 12 stress 0.2205447
## Run 13 stress 0.2186362
## Run 14 stress 0.2155166
## ... New best solution
## ... Procrustes: rmse 0.0204821 max resid 0.1305434
## Run 15 stress 0.2223445
## Run 16 stress 0.2212153
## Run 17 stress 0.2279396
## Run 18 stress 0.2229546
## Run 19 stress 0.2196029
## Run 20 stress 0.2177265
## Run 21 stress 0.2273296
## Run 22 stress 0.2263244
## Run 23 stress 0.2158204
## ... Procrustes: rmse 0.01684677 max resid 0.1265592
## Run 24 stress 0.2158691
## ... Procrustes: rmse 0.01586524 max resid 0.1269345
## Run 25 stress 0.2159578
## ... Procrustes: rmse 0.02447305 max resid 0.1655043
## Run 26 stress 0.2269548
## Run 27 stress 0.2186059
## Run 28 stress 0.2167072
## Run 29 stress 0.225939
## Run 30 stress 0.2236811
## Run 31 stress 0.2238592
## Run 32 stress 0.2319865
## Run 33 stress 0.2159096
## ... Procrustes: rmse 0.0184587 max resid 0.123545
## Run 34 stress 0.2273746
## Run 35 stress 0.217599
## Run 36 stress 0.2230669
## Run 37 stress 0.2157658
## ... Procrustes: rmse 0.0164092 max resid 0.1260331
## Run 38 stress 0.2326864
## Run 39 stress 0.2184195
## Run 40 stress 0.2250379
## Run 41 stress 0.2206022
## Run 42 stress 0.2203873
## Run 43 stress 0.21509
## ... New best solution
## ... Procrustes: rmse 0.009749678 max resid 0.0930641
## Run 44 stress 0.2251854
## Run 45 stress 0.2152085
## ... Procrustes: rmse 0.01063198 max resid 0.09361821
## Run 46 stress 0.230889
## Run 47 stress 0.2265384
## Run 48 stress 0.2157705
## Run 49 stress 0.2264462
## Run 50 stress 0.2234839
## Run 51 stress 0.2150887
## ... New best solution
## ... Procrustes: rmse 0.002932656 max resid 0.02854326
## Run 52 stress 0.2269844
## Run 53 stress 0.2159584
## Run 54 stress 0.2150659
## ... New best solution
## ... Procrustes: rmse 0.006628404 max resid 0.0564706
## Run 55 stress 0.2158582
## Run 56 stress 0.2149768
## ... New best solution
## ... Procrustes: rmse 0.008035855 max resid 0.09110704
## Run 57 stress 0.2220072
## Run 58 stress 0.2265685
## Run 59 stress 0.2237338
## Run 60 stress 0.2165346
## Run 61 stress 0.2261638
## Run 62 stress 0.2189837
## Run 63 stress 0.2206557
## Run 64 stress 0.2162196
## Run 65 stress 0.2245364
## Run 66 stress 0.2338965
## Run 67 stress 0.220529
## Run 68 stress 0.2191572
## Run 69 stress 0.2277567
## Run 70 stress 0.2195893
## Run 71 stress 0.2361302
## Run 72 stress 0.2240511
## Run 73 stress 0.2272782
## Run 74 stress 0.226884
## Run 75 stress 0.2318863
## Run 76 stress 0.2204092
## Run 77 stress 0.2205332
## Run 78 stress 0.2258159
## Run 79 stress 0.2217336
## Run 80 stress 0.2282545
## Run 81 stress 0.2154225
## ... Procrustes: rmse 0.02054663 max resid 0.1629805
## Run 82 stress 0.2234582
## Run 83 stress 0.2207347
## Run 84 stress 0.2151586
## ... Procrustes: rmse 0.01994105 max resid 0.1633371
## Run 85 stress 0.2191923
## Run 86 stress 0.2203263
## Run 87 stress 0.2216692
## Run 88 stress 0.2253989
## Run 89 stress 0.2253323
## Run 90 stress 0.220464
## Run 91 stress 0.2162941
## Run 92 stress 0.2250935
## Run 93 stress 0.2238101
## Run 94 stress 0.2149905
## ... Procrustes: rmse 0.002122941 max resid 0.02096845
## Run 95 stress 0.2156275
## Run 96 stress 0.2188379
## Run 97 stress 0.2311717
## Run 98 stress 0.2158208
## Run 99 stress 0.2323946
## Run 100 stress 0.2159056
## Run 101 stress 0.215077
## ... Procrustes: rmse 0.0208133 max resid 0.1633742
## Run 102 stress 0.227316
## Run 103 stress 0.2247014
## Run 104 stress 0.2280357
## Run 105 stress 0.2152112
## ... Procrustes: rmse 0.02166033 max resid 0.1632986
## Run 106 stress 0.2171503
## Run 107 stress 0.2157333
## Run 108 stress 0.2269285
## Run 109 stress 0.225672
## Run 110 stress 0.2188855
## Run 111 stress 0.2196542
## Run 112 stress 0.2279677
## Run 113 stress 0.2260438
## Run 114 stress 0.227823
## Run 115 stress 0.2274096
## Run 116 stress 0.2293153
## Run 117 stress 0.2189004
## Run 118 stress 0.2269972
## Run 119 stress 0.2252907
## Run 120 stress 0.2228913
## Run 121 stress 0.2301384
## Run 122 stress 0.2197315
## Run 123 stress 0.2157674
## Run 124 stress 0.2272472
## Run 125 stress 0.2264969
## Run 126 stress 0.2172253
## Run 127 stress 0.2260523
## Run 128 stress 0.2149907
## ... Procrustes: rmse 0.01820151 max resid 0.1636488
## Run 129 stress 0.2176014
## Run 130 stress 0.2157289
## Run 131 stress 0.2220279
## Run 132 stress 0.2150576
## ... Procrustes: rmse 0.008529661 max resid 0.09122722
## Run 133 stress 0.2205514
## Run 134 stress 0.2160255
## Run 135 stress 0.2303991
## Run 136 stress 0.2240563
## Run 137 stress 0.218178
## Run 138 stress 0.2270078
## Run 139 stress 0.2160214
## Run 140 stress 0.2226718
## Run 141 stress 0.2194339
## Run 142 stress 0.2309949
## Run 143 stress 0.2201168
## Run 144 stress 0.2193319
## Run 145 stress 0.215446
## ... Procrustes: rmse 0.007658015 max resid 0.05736752
## Run 146 stress 0.2223504
## Run 147 stress 0.2242589
## Run 148 stress 0.2197097
## Run 149 stress 0.2183908
## Run 150 stress 0.2164896
## Run 151 stress 0.2256542
## Run 152 stress 0.2277777
## Run 153 stress 0.2252472
## Run 154 stress 0.2254462
## Run 155 stress 0.2297408
## Run 156 stress 0.2198868
## Run 157 stress 0.2276244
## Run 158 stress 0.2172467
## Run 159 stress 0.215485
## Run 160 stress 0.2246533
## Run 161 stress 0.2221388
## Run 162 stress 0.2150565
## ... Procrustes: rmse 0.007935467 max resid 0.09097308
## Run 163 stress 0.2311059
## Run 164 stress 0.2239454
## Run 165 stress 0.2174735
## Run 166 stress 0.223386
## Run 167 stress 0.2269042
## Run 168 stress 0.2170816
## Run 169 stress 0.2272679
## Run 170 stress 0.2218548
## Run 171 stress 0.2166919
## Run 172 stress 0.2170756
## Run 173 stress 0.2202952
## Run 174 stress 0.2275476
## Run 175 stress 0.2275909
## Run 176 stress 0.2189987
## Run 177 stress 0.225801
## Run 178 stress 0.2150034
## ... Procrustes: rmse 0.0186465 max resid 0.1621749
## Run 179 stress 0.2191152
## Run 180 stress 0.2208091
## Run 181 stress 0.233829
## Run 182 stress 0.2172286
## Run 183 stress 0.2246584
## Run 184 stress 0.2150045
## ... Procrustes: rmse 0.01820222 max resid 0.1636776
## Run 185 stress 0.2279008
## Run 186 stress 0.227053
## Run 187 stress 0.2227136
## Run 188 stress 0.2154343
## ... Procrustes: rmse 0.009770759 max resid 0.09153348
## Run 189 stress 0.2305896
## Run 190 stress 0.2191584
## Run 191 stress 0.2184892
## Run 192 stress 0.2160225
## Run 193 stress 0.2208038
## Run 194 stress 0.2150153
## ... Procrustes: rmse 0.01847285 max resid 0.1633921
## Run 195 stress 0.2169943
## Run 196 stress 0.2235824
## Run 197 stress 0.2154887
## Run 198 stress 0.2166893
## Run 199 stress 0.2243318
## Run 200 stress 0.2203675
## Run 201 stress 0.2149928
## ... Procrustes: rmse 0.001187828 max resid 0.006826871
## ... Similar to previous best
## *** Best solution repeated 1 times
##
## Call:
## metaMDS(comm = mat.dis_fish, distance = "bray", k = 2, trymax = 500)
##
## global Multidimensional Scaling using monoMDS
##
## Data: mat.dis_fish
## Distance: bray
##
## Dimensions: 2
## Stress: 0.2149768
## Stress type 1, weak ties
## Best solution was repeated 1 time in 201 tries
## The best solution was from try 56 (random start)
## Scaling: centring, PC rotation, halfchange scaling
## Species: scores missing
## NMDS1 NMDS2 Site
## 1 -0.004064164 -0.10263879 1
## 2 0.267454706 -0.19319746 1
## 3 -0.285906457 -0.26111624 1
## 4 0.367455621 -0.10344401 1
## 5 -0.237371608 -0.06398577 1
## 6 0.185030534 -0.41500430 1## $vectors
## NMDS1 NMDS2 r2 Pr(>r)
## Acanthurus nigrofuscus 0.93887 0.34428 0.0540 0.024 *
## Caranx melampygus -0.47354 0.88077 0.0047 0.726
## Chaetodon vagabundus -0.97861 0.20575 0.2236 0.001 ***
## Chlorurus spilurus 0.92711 0.37479 0.0056 0.604
## Gomphosus varius 0.23095 -0.97296 0.1814 0.001 ***
## Halichoeres trimaculatus 0.16218 0.98676 0.2551 0.001 ***
## Mulloidichthys flavolineatus 0.04282 0.99908 0.0275 0.128
## Parupeneus multifasciatus 0.99892 -0.04656 0.0218 0.198
## Rhinecanthus aculeatus 0.37261 0.92799 0.2342 0.001 ***
## Stegastes sp 0.25758 -0.96626 0.4134 0.001 ***
## Stethojulis bandanensis 0.14364 0.98963 0.2269 0.001 ***
## Thalassoma hardwicke 0.59718 -0.80211 0.0920 0.002 **
## Acanthurus triostegus -0.99918 -0.04056 0.0503 0.041 *
## Chaetodon ephippium 0.54354 -0.83939 0.0367 0.078 .
## Chaetodon lunula 0.27797 -0.96059 0.0851 0.003 **
## Chaetodon ulietensis 0.18323 -0.98307 0.0203 0.241
## Epinephelus merra 0.64520 -0.76401 0.0376 0.076 .
## Zebrasoma scopas 0.55633 -0.83096 0.0476 0.036 *
## Carcharhinus melanopterus -0.59456 -0.80405 0.0515 0.030 *
## Labroides dimidiatus -0.13136 -0.99133 0.0711 0.012 *
## Scarus psittacus 0.04773 0.99886 0.2596 0.001 ***
## Balistapus undulatus 0.59258 -0.80551 0.0961 0.001 ***
## Centropyge flavissima 0.90788 0.41923 0.0133 0.338
## Chaetodon citrinellus 0.98293 0.18396 0.0200 0.232
## Cheilinus chlorourus 0.24380 0.96982 0.1024 0.001 ***
## Cheilinus trilobatus 0.76831 -0.64008 0.0820 0.006 **
## Naso lituratus -0.20177 0.97943 0.0041 0.704
## Cheilio inermis 0.56522 0.82494 0.0610 0.010 **
## Fistularia commersonii -0.01740 -0.99985 0.0153 0.303
## Cephalopholis argus -0.50731 -0.86176 0.0111 0.410
## Chaetodon auriga 0.32853 -0.94449 0.0419 0.053 .
## Chaetodon reticulatus -0.98482 0.17359 0.0084 0.476
## Cheilinus undulatus -0.98482 0.17359 0.0084 0.476
## Epibulus insidiator 0.73433 -0.67879 0.0191 0.257
## Siganus spinus 0.21826 0.97589 0.1083 0.002 **
## Chaetodon lunulatus 0.55506 -0.83181 0.0463 0.043 *
## Abudefduf sexfasciatus 0.99628 -0.08621 0.0729 0.007 **
## Parupeneus insularis 0.14603 0.98928 0.0057 0.634
## Scarus forsteni -0.10335 -0.99465 0.0053 0.598
## Abudefduf septemfasciatus -0.19823 -0.98016 0.0127 0.358
## Hipposcarus longiceps -0.97164 -0.23647 0.0099 0.395
## Zanclus cornutus 0.80568 0.59235 0.0240 0.161
## Chrysiptera brownriggii 0.67740 -0.73562 0.0149 0.333
## Ostracion meleagris -0.01080 -0.99994 0.0007 0.944
## Pseudocheilinus evanidus 0.89447 -0.44712 0.0016 0.874
## Ellochelon vaigiensis -0.17704 0.98420 0.0017 0.839
## Chaetodon trifascialis 0.83146 0.55558 0.0010 0.926
## Himantura fai -0.99980 0.02002 0.0358 0.086 .
## Scarus oviceps 0.63633 -0.77142 0.0125 0.339
## Acanthurus guttatus -0.97988 0.19960 0.0135 0.343
## Wrasse Unknown 0.04185 -0.99912 0.1093 0.003 **
## Chaetodon ornatissimus 0.51708 -0.85594 0.0121 0.329
## Oxycheilinus unifasciatus 0.76598 0.64286 0.0135 0.379
## Mulloidichthys vanicolensis 0.27826 0.96051 0.0761 0.014 *
## Aulostomus chinensis 0.41077 0.91174 0.0095 0.482
## Ostracion cubicus 0.26448 0.96439 0.0147 0.289
## Scarus ghobban 0.13174 0.99128 0.0300 0.132
## Ostorhinchus nigrofasciatus -0.18245 0.98322 0.0054 0.659
## Parrotfish Unknonwn 0.84941 0.52773 0.0143 0.315
## Lethrinus olivaceus -0.33999 0.94043 0.0033 0.781
## Parupeneus ciliatus 0.25607 0.96666 0.0203 0.213
## Lutjanus fulvus 0.99866 -0.05184 0.0009 0.909
## Gymnothorax javanicus -0.20202 0.97938 0.0006 0.959
## Chromis viridis 0.90131 0.43318 0.1048 0.002 **
## Coris aygula 0.82754 0.56141 0.0130 0.332
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## $factors
## NULL
##
## $na.action
## function (object, ...)
## UseMethod("na.action")
## <bytecode: 0x1433b0778>
## <environment: namespace:stats>## NMDS1 NMDS2 Species
## Acanthurus nigrofuscus 0.21816869 0.08000175 Acanthurus nigrofuscus
## Caranx melampygus -0.03247482 0.06040288 Caranx melampygus
## Chaetodon vagabundus -0.46269691 0.09727946 Chaetodon vagabundus
## Chlorurus spilurus 0.06935297 0.02803666 Chlorurus spilurus
## Gomphosus varius 0.09837481 -0.41443497 Gomphosus varius
## Halichoeres trimaculatus 0.08191603 0.49839086 Halichoeres trimaculatus
## NMDS1 NMDS2
## Acanthurus nigrofuscus 0.21816869 0.080001748
## Chaetodon vagabundus -0.46269691 0.097279458
## Gomphosus varius 0.09837481 -0.414434969
## Halichoeres trimaculatus 0.08191603 0.498390862
## Rhinecanthus aculeatus 0.18031143 0.449062333
## Stegastes sp 0.16561972 -0.621282890
## Stethojulis bandanensis 0.06841722 0.471371283
## Thalassoma hardwicke 0.18113163 -0.243291536
## Acanthurus triostegus -0.22401051 -0.009092526
## Chaetodon lunula 0.08110616 -0.280277807
## Zebrasoma scopas 0.12135133 -0.181257281
## Carcharhinus melanopterus -0.13486172 -0.182381937
## Labroides dimidiatus -0.03501469 -0.264246953
## Scarus psittacus 0.02432246 0.508966389
## Balistapus undulatus 0.18366845 -0.249663985
## Cheilinus chlorourus 0.07803457 0.310411529
## Cheilinus trilobatus 0.22003703 -0.183311452
## Cheilio inermis 0.13958498 0.203726704
## Siganus spinus 0.07182504 0.321145339
## Chaetodon lunulatus 0.11945444 -0.179015830
## Abudefduf sexfasciatus 0.26900421 -0.023278745
## Wrasse Unknown 0.01383391 -0.330283389
## Mulloidichthys vanicolensis 0.07678177 0.265038730
## Chromis viridis 0.29184467 0.140264800
## Species pval
## Acanthurus nigrofuscus Acanthurus nigrofuscus 0.024
## Chaetodon vagabundus Chaetodon vagabundus 0.001
## Gomphosus varius Gomphosus varius 0.001
## Halichoeres trimaculatus Halichoeres trimaculatus 0.001
## Rhinecanthus aculeatus Rhinecanthus aculeatus 0.001
## Stegastes sp Stegastes sp 0.001
## Stethojulis bandanensis Stethojulis bandanensis 0.001
## Thalassoma hardwicke Thalassoma hardwicke 0.002
## Acanthurus triostegus Acanthurus triostegus 0.041
## Chaetodon lunula Chaetodon lunula 0.003
## Zebrasoma scopas Zebrasoma scopas 0.036
## Carcharhinus melanopterus Carcharhinus melanopterus 0.030
## Labroides dimidiatus Labroides dimidiatus 0.012
## Scarus psittacus Scarus psittacus 0.001
## Balistapus undulatus Balistapus undulatus 0.001
## Cheilinus chlorourus Cheilinus chlorourus 0.001
## Cheilinus trilobatus Cheilinus trilobatus 0.006
## Cheilio inermis Cheilio inermis 0.010
## Siganus spinus Siganus spinus 0.002
## Chaetodon lunulatus Chaetodon lunulatus 0.043
## Abudefduf sexfasciatus Abudefduf sexfasciatus 0.007
## Wrasse Unknown Wrasse Unknown 0.003
## Mulloidichthys vanicolensis Mulloidichthys vanicolensis 0.014
## Chromis viridis Chromis viridis 0.002
Calculating richness against gradient metrics:
Calculating diversity against gradient metrics:
